About
Highly analytical and data-driven Software Engineer with 2+ years of experience, specializing in data labeling, quality assurance, and AI/ML techniques. Proven ability to act as a Subject Matter Expert, optimize complex workflows, and deliver actionable insights for product enhancement, aligning with Meta's Data Labeling Analyst objectives. Excels in critical analysis, strategic organization, and cross-functional communication to drive operational excellence and improve data quality in ambiguous environments.
Work
Buffalo, New York, US
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Summary
Led the implementation and optimization of data labeling and quality-control pipelines to ensure reliable input for advanced NLP and LLM research.
Highlights
Spearheaded the implementation of data labeling and quality-control pipelines, ensuring high-fidelity input crucial for cutting-edge NLP and LLM research initiatives.
Conducted rigorous quality audits and generated comprehensive labeling metrics, transforming data into actionable insights that significantly improved operational KPIs.
Served as a Subject Matter Expert for intricate labeling workflows, developing clear reproducibility guides and comprehensive workflow documentation.
Collaborated effectively with cross-functional teams to resolve tooling issues and integrate approved workflow updates, enhancing overall operational efficiency.
Buffalo, New York, US
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Summary
Developed robust backend systems and optimized data processing workflows to enable real-time collaborative labeling and analytics for product teams.
Highlights
Engineered REST APIs and microservices for scalable structured data ingestion and transformation, facilitating real-time collaborative labeling and analytics.
Cultivated strong vendor relationships, participating in weekly business reviews to proactively resolve quality and technical barriers.
Identified and implemented process optimizations that successfully reduced data-retrieval latency by 20%, significantly enhancing system efficiency.
Leveraged Excel, SQL, and Python for in-depth analysis of large datasets, delivering data-driven dashboards to inform strategic decisions.
Buffalo, New York, US
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Summary
Contributed to the development of a collaborative code editor, focusing on backend logic for real-time data synchronization and scalable architecture.
Highlights
Developed backend logic for a collaborative code editor, implementing real-time data synchronization and version tracking functionalities.
Applied object-oriented principles and modular architecture to build scalable data workflows, enhancing system adaptability and maintainability.
Diagnosed and resolved root causes of latency issues within a distributed editing environment, significantly improving system performance.
Skills
Programming Languages
Java, Python, C++, JavaScript, SQL.
Frameworks/Tools
React, Redux, Flask, Docker, Jenkins, Git, Airflow, VS Code, Power BI, Excel.
Cloud & AI/ML Technologies
AI, ML, LLM, DL, CNN, NLP, Computer Vision, AWS, GCP, Azure, CI/CD, Kubernetes.
Data & Big Data
Hadoop, Big Query, Spark, ETL/ELT, Kafka, EventHub, MySQL, PostgreSQL, MongoDB, NoSQL.
Concepts & Methodologies
Data Engineering, ETL Pipelines, Distributed Systems, Scalability, Latency Optimization, Agile, Critical Analysis, Strategic Planning, Stakeholder Management, Communication, Problem Solving, Quality Assurance, Workflow Optimization.